Ready to get started?

Learn more about the CData Python Connector for FinancialForce or download a free trial:

Download Now

Use Dash to Build to Web Apps on FinancialForce Data

The CData Python Connector for FinancialForce enables you to create Python applications that use pandas and Dash to build FinancialForce-connected web apps.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for FinancialForce, the pandas module, and the Dash framework, you can build FinancialForce-connected web applications for FinancialForce data. This article shows how to connect to FinancialForce with the CData Connector and use pandas and Dash to build a simple web app for visualizing FinancialForce data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live FinancialForce data in Python. When you issue complex SQL queries from FinancialForce, the driver pushes supported SQL operations, like filters and aggregations, directly to FinancialForce and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to FinancialForce Data

Connecting to FinancialForce data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

There are several authentication methods available for connecting to FinancialForce: login credentials, SSO, and OAuth.

Authenticating with a Login and Token

Set the User and Password to your login credentials. Additionally, set the SecurityToken. By default, the SecurityToken is required, but you can make it optional by allowing a range of trusted IP addresses.

To disable the security token:

  1. Log in to FinancialForce and enter "Network Access" in the Quick Find box in the setup section.
  2. Add your IP address to the list of trusted IP addresses.

To obtain the security token:

  1. Open the personal information page on FinancialForce.com.
  2. Click the link to reset your security token. The token will be emailed to you.
  3. Specify the security token in the SecurityToken connection property or append it to the Password.

Authenticating with OAuth

If you do not have access to the user name and password or do not want to require them, use the OAuth user consent flow. See the OAuth section in the Help for an authentication guide.

Connecting to FinancialForce Sandbox Accounts

Set UseSandbox to true (false by default) to use a FinancialForce sandbox account. Ensure that you specify a sandbox user name in User.

After installing the CData FinancialForce Connector, follow the procedure below to install the other required modules and start accessing FinancialForce through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install pandas
pip install dash
pip install dash-daq

Visualize FinancialForce Data in Python

Once the required modules and frameworks are installed, we are ready to build our web app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.financialforce as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData FinancialForce Connector to create a connection for working with FinancialForce data.

cnxn = mod.connect("User=myUser;Password=myPassword;Security Token=myToken;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to FinancialForce

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT BillingState, Name FROM Account WHERE Industry = 'Floppy Disks'", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-financialforceedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our FinancialForce data and configure the app layout.

trace = go.Bar(x=df.BillingState, y=df.Name, name='BillingState')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='FinancialForce Account Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
    app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the FinancialForce data.

python financialforce-dash.py

Free Trial & More Information

Download a free, 30-day trial of the FinancialForce Python Connector to start building Python apps with connectivity to FinancialForce data. Reach out to our Support Team if you have any questions.



Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.financialforce as mod
import plotly.graph_objs as go

cnxn = mod.connect("User=myUser;Password=myPassword;Security Token=myToken;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT BillingState, Name FROM Account WHERE Industry = 'Floppy Disks'", cnxn)
app_name = 'dash-financialforcedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df.BillingState, y=df.Name, name='BillingState')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='FinancialForce Account Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
    app.run_server(debug=True)